{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "from sklearn.metrics import mean_squared_error as mse\n",
    "from sklearn.preprocessing import Imputer\n",
    "from sklearn.preprocessing import LabelBinarizer,OneHotEncoder\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from pylab import mpl\n",
    "mpl.rcParams['font.sans-serif'] = ['FangSong'] # 指定默认字体\n",
    "mpl.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题\n",
    "mpl.rcParams['axes.titlesize'] = 16\n",
    "\n",
    "# 设置jupyter数据框最大显示的列数\n",
    "pd.set_option('max_columns',100)\n",
    "import operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_data = pd.read_csv('../train_data_mul.csv',encoding='gb2312',index_col='id')\n",
    "targets = pd.read_csv('../targets.csv',encoding='gb2312',index_col='id')\n",
    "feature_importance = pd.read_csv('../feature_importance.csv',encoding='gb2312')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# train_data.drop(['体检日期'],axis=1,inplace=True)\n",
    "# feature_importance.loc[:400]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年龄*年龄</th>\n",
       "      <th>年龄**天门冬氨酸氨基转换酶</th>\n",
       "      <th>年龄**丙氨酸氨基转换酶</th>\n",
       "      <th>年龄**碱性磷酸酶</th>\n",
       "      <th>年龄**r-谷氨酰基转换酶</th>\n",
       "      <th>年龄**总蛋白</th>\n",
       "      <th>年龄*白蛋白</th>\n",
       "      <th>年龄**球蛋白</th>\n",
       "      <th>年龄*白球比例</th>\n",
       "      <th>年龄*甘油三酯</th>\n",
       "      <th>年龄*总胆固醇</th>\n",
       "      <th>年龄*高密度脂蛋白胆固醇</th>\n",
       "      <th>年龄*低密度脂蛋白胆固醇</th>\n",
       "      <th>年龄*尿素</th>\n",
       "      <th>年龄*肌酐</th>\n",
       "      <th>年龄*尿酸</th>\n",
       "      <th>年龄*乙肝表面抗原</th>\n",
       "      <th>年龄*乙肝表面抗体</th>\n",
       "      <th>年龄*乙肝e抗原</th>\n",
       "      <th>年龄*乙肝e抗体</th>\n",
       "      <th>年龄*乙肝核心抗体</th>\n",
       "      <th>年龄*白细胞计数</th>\n",
       "      <th>年龄*红细胞计数</th>\n",
       "      <th>年龄*血红蛋白</th>\n",
       "      <th>年龄*红细胞压积</th>\n",
       "      <th>年龄*红细胞平均体积</th>\n",
       "      <th>年龄*红细胞平均血红蛋白量</th>\n",
       "      <th>年龄*红细胞平均血红蛋白浓度</th>\n",
       "      <th>年龄*红细胞体积分布宽度</th>\n",
       "      <th>年龄*血小板计数</th>\n",
       "      <th>年龄*血小板平均体积</th>\n",
       "      <th>年龄*血小板体积分布宽度</th>\n",
       "      <th>年龄*血小板比积</th>\n",
       "      <th>年龄*中性粒细胞%</th>\n",
       "      <th>年龄*淋巴细胞%</th>\n",
       "      <th>年龄*单核细胞%</th>\n",
       "      <th>年龄*嗜酸细胞%</th>\n",
       "      <th>年龄*嗜碱细胞%</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**天门冬氨酸氨基转换酶</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**丙氨酸氨基转换酶</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**碱性磷酸酶</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**r-谷氨酰基转换酶</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**总蛋白</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*白蛋白</th>\n",
       "      <th>*天门冬氨酸氨基转换酶**球蛋白</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*白球比例</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*甘油三酯</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*总胆固醇</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*高密度脂蛋白胆固醇</th>\n",
       "      <th>*天门冬氨酸氨基转换酶*低密度脂蛋白胆固醇</th>\n",
       "      <th>...</th>\n",
       "      <th>红细胞体积分布宽度*淋巴细胞%</th>\n",
       "      <th>红细胞体积分布宽度*单核细胞%</th>\n",
       "      <th>红细胞体积分布宽度*嗜酸细胞%</th>\n",
       "      <th>红细胞体积分布宽度*嗜碱细胞%</th>\n",
       "      <th>血小板计数*血小板计数</th>\n",
       "      <th>血小板计数*血小板平均体积</th>\n",
       "      <th>血小板计数*血小板体积分布宽度</th>\n",
       "      <th>血小板计数*血小板比积</th>\n",
       "      <th>血小板计数*中性粒细胞%</th>\n",
       "      <th>血小板计数*淋巴细胞%</th>\n",
       "      <th>血小板计数*单核细胞%</th>\n",
       "      <th>血小板计数*嗜酸细胞%</th>\n",
       "      <th>血小板计数*嗜碱细胞%</th>\n",
       "      <th>血小板平均体积*血小板平均体积</th>\n",
       "      <th>血小板平均体积*血小板体积分布宽度</th>\n",
       "      <th>血小板平均体积*血小板比积</th>\n",
       "      <th>血小板平均体积*中性粒细胞%</th>\n",
       "      <th>血小板平均体积*淋巴细胞%</th>\n",
       "      <th>血小板平均体积*单核细胞%</th>\n",
       "      <th>血小板平均体积*嗜酸细胞%</th>\n",
       "      <th>血小板平均体积*嗜碱细胞%</th>\n",
       "      <th>血小板体积分布宽度*血小板体积分布宽度</th>\n",
       "      <th>血小板体积分布宽度*血小板比积</th>\n",
       "      <th>血小板体积分布宽度*中性粒细胞%</th>\n",
       "      <th>血小板体积分布宽度*淋巴细胞%</th>\n",
       "      <th>血小板体积分布宽度*单核细胞%</th>\n",
       "      <th>血小板体积分布宽度*嗜酸细胞%</th>\n",
       "      <th>血小板体积分布宽度*嗜碱细胞%</th>\n",
       "      <th>血小板比积*血小板比积</th>\n",
       "      <th>血小板比积*中性粒细胞%</th>\n",
       "      <th>血小板比积*淋巴细胞%</th>\n",
       "      <th>血小板比积*单核细胞%</th>\n",
       "      <th>血小板比积*嗜酸细胞%</th>\n",
       "      <th>血小板比积*嗜碱细胞%</th>\n",
       "      <th>中性粒细胞%*中性粒细胞%</th>\n",
       "      <th>中性粒细胞%*淋巴细胞%</th>\n",
       "      <th>中性粒细胞%*单核细胞%</th>\n",
       "      <th>中性粒细胞%*嗜酸细胞%</th>\n",
       "      <th>中性粒细胞%*嗜碱细胞%</th>\n",
       "      <th>淋巴细胞%*淋巴细胞%</th>\n",
       "      <th>淋巴细胞%*单核细胞%</th>\n",
       "      <th>淋巴细胞%*嗜酸细胞%</th>\n",
       "      <th>淋巴细胞%*嗜碱细胞%</th>\n",
       "      <th>单核细胞%*单核细胞%</th>\n",
       "      <th>单核细胞%*嗜酸细胞%</th>\n",
       "      <th>单核细胞%*嗜碱细胞%</th>\n",
       "      <th>嗜酸细胞%*嗜酸细胞%</th>\n",
       "      <th>嗜酸细胞%*嗜碱细胞%</th>\n",
       "      <th>嗜碱细胞%*嗜碱细胞%</th>\n",
       "      <th>年龄</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1681</td>\n",
       "      <td>1023.36</td>\n",
       "      <td>947.10</td>\n",
       "      <td>4083.19</td>\n",
       "      <td>829.43</td>\n",
       "      <td>3152.08</td>\n",
       "      <td>2033.60</td>\n",
       "      <td>1118.48</td>\n",
       "      <td>74.62</td>\n",
       "      <td>53.71</td>\n",
       "      <td>181.63</td>\n",
       "      <td>56.17</td>\n",
       "      <td>108.65</td>\n",
       "      <td>240.67</td>\n",
       "      <td>3167.25</td>\n",
       "      <td>14324.99</td>\n",
       "      <td>2.05</td>\n",
       "      <td>125.665</td>\n",
       "      <td>1.64</td>\n",
       "      <td>67.24</td>\n",
       "      <td>68.47</td>\n",
       "      <td>218.94</td>\n",
       "      <td>213.61</td>\n",
       "      <td>6810.1</td>\n",
       "      <td>19.639</td>\n",
       "      <td>3767.9</td>\n",
       "      <td>1307.9</td>\n",
       "      <td>14227.0</td>\n",
       "      <td>524.8</td>\n",
       "      <td>6806.0</td>\n",
       "      <td>405.9</td>\n",
       "      <td>713.4</td>\n",
       "      <td>6.724</td>\n",
       "      <td>2218.1</td>\n",
       "      <td>1402.2</td>\n",
       "      <td>266.5</td>\n",
       "      <td>192.7</td>\n",
       "      <td>24.6</td>\n",
       "      <td>623.0016</td>\n",
       "      <td>576.5760</td>\n",
       "      <td>2485.7664</td>\n",
       "      <td>504.9408</td>\n",
       "      <td>1918.9248</td>\n",
       "      <td>1238.0160</td>\n",
       "      <td>680.9088</td>\n",
       "      <td>45.4272</td>\n",
       "      <td>32.6976</td>\n",
       "      <td>110.5728</td>\n",
       "      <td>34.1952</td>\n",
       "      <td>66.1440</td>\n",
       "      <td>...</td>\n",
       "      <td>437.76</td>\n",
       "      <td>83.20</td>\n",
       "      <td>60.16</td>\n",
       "      <td>7.68</td>\n",
       "      <td>27556.0</td>\n",
       "      <td>1643.4</td>\n",
       "      <td>2888.4</td>\n",
       "      <td>27.224</td>\n",
       "      <td>8980.6</td>\n",
       "      <td>5677.2</td>\n",
       "      <td>1079.0</td>\n",
       "      <td>780.2</td>\n",
       "      <td>99.6</td>\n",
       "      <td>98.01</td>\n",
       "      <td>172.26</td>\n",
       "      <td>1.6236</td>\n",
       "      <td>535.59</td>\n",
       "      <td>338.58</td>\n",
       "      <td>64.35</td>\n",
       "      <td>46.53</td>\n",
       "      <td>5.94</td>\n",
       "      <td>302.76</td>\n",
       "      <td>2.8536</td>\n",
       "      <td>941.34</td>\n",
       "      <td>595.08</td>\n",
       "      <td>113.10</td>\n",
       "      <td>81.78</td>\n",
       "      <td>10.44</td>\n",
       "      <td>0.026896</td>\n",
       "      <td>8.8724</td>\n",
       "      <td>5.6088</td>\n",
       "      <td>1.0660</td>\n",
       "      <td>0.7708</td>\n",
       "      <td>0.0984</td>\n",
       "      <td>2926.81</td>\n",
       "      <td>1850.22</td>\n",
       "      <td>351.65</td>\n",
       "      <td>254.27</td>\n",
       "      <td>32.46</td>\n",
       "      <td>1169.64</td>\n",
       "      <td>222.30</td>\n",
       "      <td>160.74</td>\n",
       "      <td>20.52</td>\n",
       "      <td>42.25</td>\n",
       "      <td>30.55</td>\n",
       "      <td>3.90</td>\n",
       "      <td>22.09</td>\n",
       "      <td>2.82</td>\n",
       "      <td>0.36</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1681</td>\n",
       "      <td>1007.37</td>\n",
       "      <td>1486.25</td>\n",
       "      <td>2755.61</td>\n",
       "      <td>3239.00</td>\n",
       "      <td>3256.63</td>\n",
       "      <td>1958.16</td>\n",
       "      <td>1298.47</td>\n",
       "      <td>61.91</td>\n",
       "      <td>115.21</td>\n",
       "      <td>166.46</td>\n",
       "      <td>38.13</td>\n",
       "      <td>107.83</td>\n",
       "      <td>215.66</td>\n",
       "      <td>3571.92</td>\n",
       "      <td>19957.98</td>\n",
       "      <td>2.05</td>\n",
       "      <td>125.665</td>\n",
       "      <td>1.64</td>\n",
       "      <td>67.24</td>\n",
       "      <td>68.47</td>\n",
       "      <td>313.65</td>\n",
       "      <td>213.61</td>\n",
       "      <td>6396.0</td>\n",
       "      <td>18.696</td>\n",
       "      <td>3587.5</td>\n",
       "      <td>1225.9</td>\n",
       "      <td>14022.0</td>\n",
       "      <td>549.4</td>\n",
       "      <td>11357.0</td>\n",
       "      <td>377.2</td>\n",
       "      <td>422.3</td>\n",
       "      <td>10.660</td>\n",
       "      <td>2132.0</td>\n",
       "      <td>1504.7</td>\n",
       "      <td>237.8</td>\n",
       "      <td>192.7</td>\n",
       "      <td>32.8</td>\n",
       "      <td>603.6849</td>\n",
       "      <td>890.6625</td>\n",
       "      <td>1651.3497</td>\n",
       "      <td>1941.0300</td>\n",
       "      <td>1951.5951</td>\n",
       "      <td>1173.4632</td>\n",
       "      <td>778.1319</td>\n",
       "      <td>37.1007</td>\n",
       "      <td>69.0417</td>\n",
       "      <td>99.7542</td>\n",
       "      <td>22.8501</td>\n",
       "      <td>64.6191</td>\n",
       "      <td>...</td>\n",
       "      <td>491.78</td>\n",
       "      <td>77.72</td>\n",
       "      <td>62.98</td>\n",
       "      <td>10.72</td>\n",
       "      <td>76729.0</td>\n",
       "      <td>2548.4</td>\n",
       "      <td>2853.1</td>\n",
       "      <td>72.020</td>\n",
       "      <td>14404.0</td>\n",
       "      <td>10165.9</td>\n",
       "      <td>1606.6</td>\n",
       "      <td>1301.9</td>\n",
       "      <td>221.6</td>\n",
       "      <td>84.64</td>\n",
       "      <td>94.76</td>\n",
       "      <td>2.3920</td>\n",
       "      <td>478.40</td>\n",
       "      <td>337.64</td>\n",
       "      <td>53.36</td>\n",
       "      <td>43.24</td>\n",
       "      <td>7.36</td>\n",
       "      <td>106.09</td>\n",
       "      <td>2.6780</td>\n",
       "      <td>535.60</td>\n",
       "      <td>378.01</td>\n",
       "      <td>59.74</td>\n",
       "      <td>48.41</td>\n",
       "      <td>8.24</td>\n",
       "      <td>0.067600</td>\n",
       "      <td>13.5200</td>\n",
       "      <td>9.5420</td>\n",
       "      <td>1.5080</td>\n",
       "      <td>1.2220</td>\n",
       "      <td>0.2080</td>\n",
       "      <td>2704.00</td>\n",
       "      <td>1908.40</td>\n",
       "      <td>301.60</td>\n",
       "      <td>244.40</td>\n",
       "      <td>41.60</td>\n",
       "      <td>1346.89</td>\n",
       "      <td>212.86</td>\n",
       "      <td>172.49</td>\n",
       "      <td>29.36</td>\n",
       "      <td>33.64</td>\n",
       "      <td>27.26</td>\n",
       "      <td>4.64</td>\n",
       "      <td>22.09</td>\n",
       "      <td>3.76</td>\n",
       "      <td>0.64</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2116</td>\n",
       "      <td>957.72</td>\n",
       "      <td>700.58</td>\n",
       "      <td>2929.74</td>\n",
       "      <td>1755.82</td>\n",
       "      <td>3966.58</td>\n",
       "      <td>2208.00</td>\n",
       "      <td>1758.58</td>\n",
       "      <td>57.96</td>\n",
       "      <td>45.54</td>\n",
       "      <td>189.98</td>\n",
       "      <td>75.44</td>\n",
       "      <td>92.46</td>\n",
       "      <td>219.42</td>\n",
       "      <td>3596.74</td>\n",
       "      <td>20795.22</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.920</td>\n",
       "      <td>0.46</td>\n",
       "      <td>63.02</td>\n",
       "      <td>49.22</td>\n",
       "      <td>211.60</td>\n",
       "      <td>218.96</td>\n",
       "      <td>6844.8</td>\n",
       "      <td>20.148</td>\n",
       "      <td>4227.4</td>\n",
       "      <td>1439.8</td>\n",
       "      <td>15640.0</td>\n",
       "      <td>598.0</td>\n",
       "      <td>11086.0</td>\n",
       "      <td>381.8</td>\n",
       "      <td>763.6</td>\n",
       "      <td>9.154</td>\n",
       "      <td>2212.6</td>\n",
       "      <td>1853.8</td>\n",
       "      <td>354.2</td>\n",
       "      <td>147.2</td>\n",
       "      <td>36.8</td>\n",
       "      <td>433.4724</td>\n",
       "      <td>317.0886</td>\n",
       "      <td>1326.0258</td>\n",
       "      <td>794.6994</td>\n",
       "      <td>1795.3086</td>\n",
       "      <td>999.3600</td>\n",
       "      <td>795.9486</td>\n",
       "      <td>26.2332</td>\n",
       "      <td>20.6118</td>\n",
       "      <td>85.9866</td>\n",
       "      <td>34.1448</td>\n",
       "      <td>41.8482</td>\n",
       "      <td>...</td>\n",
       "      <td>523.90</td>\n",
       "      <td>100.10</td>\n",
       "      <td>41.60</td>\n",
       "      <td>10.40</td>\n",
       "      <td>58081.0</td>\n",
       "      <td>2000.3</td>\n",
       "      <td>4000.6</td>\n",
       "      <td>47.959</td>\n",
       "      <td>11592.1</td>\n",
       "      <td>9712.3</td>\n",
       "      <td>1855.7</td>\n",
       "      <td>771.2</td>\n",
       "      <td>192.8</td>\n",
       "      <td>68.89</td>\n",
       "      <td>137.78</td>\n",
       "      <td>1.6517</td>\n",
       "      <td>399.23</td>\n",
       "      <td>334.49</td>\n",
       "      <td>63.91</td>\n",
       "      <td>26.56</td>\n",
       "      <td>6.64</td>\n",
       "      <td>275.56</td>\n",
       "      <td>3.3034</td>\n",
       "      <td>798.46</td>\n",
       "      <td>668.98</td>\n",
       "      <td>127.82</td>\n",
       "      <td>53.12</td>\n",
       "      <td>13.28</td>\n",
       "      <td>0.039601</td>\n",
       "      <td>9.5719</td>\n",
       "      <td>8.0197</td>\n",
       "      <td>1.5323</td>\n",
       "      <td>0.6368</td>\n",
       "      <td>0.1592</td>\n",
       "      <td>2313.61</td>\n",
       "      <td>1938.43</td>\n",
       "      <td>370.37</td>\n",
       "      <td>153.92</td>\n",
       "      <td>38.48</td>\n",
       "      <td>1624.09</td>\n",
       "      <td>310.31</td>\n",
       "      <td>128.96</td>\n",
       "      <td>32.24</td>\n",
       "      <td>59.29</td>\n",
       "      <td>24.64</td>\n",
       "      <td>6.16</td>\n",
       "      <td>10.24</td>\n",
       "      <td>2.56</td>\n",
       "      <td>0.64</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>484</td>\n",
       "      <td>329.78</td>\n",
       "      <td>232.98</td>\n",
       "      <td>1629.76</td>\n",
       "      <td>444.84</td>\n",
       "      <td>1561.56</td>\n",
       "      <td>968.44</td>\n",
       "      <td>593.12</td>\n",
       "      <td>35.86</td>\n",
       "      <td>23.32</td>\n",
       "      <td>151.58</td>\n",
       "      <td>31.46</td>\n",
       "      <td>110.88</td>\n",
       "      <td>93.06</td>\n",
       "      <td>1352.12</td>\n",
       "      <td>8114.70</td>\n",
       "      <td>1.10</td>\n",
       "      <td>67.430</td>\n",
       "      <td>0.88</td>\n",
       "      <td>36.08</td>\n",
       "      <td>36.74</td>\n",
       "      <td>205.92</td>\n",
       "      <td>94.38</td>\n",
       "      <td>3014.0</td>\n",
       "      <td>8.866</td>\n",
       "      <td>2065.8</td>\n",
       "      <td>701.8</td>\n",
       "      <td>7480.0</td>\n",
       "      <td>277.2</td>\n",
       "      <td>5544.0</td>\n",
       "      <td>226.6</td>\n",
       "      <td>237.6</td>\n",
       "      <td>5.720</td>\n",
       "      <td>917.4</td>\n",
       "      <td>1023.0</td>\n",
       "      <td>147.4</td>\n",
       "      <td>101.2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>224.7001</td>\n",
       "      <td>158.7441</td>\n",
       "      <td>1110.4592</td>\n",
       "      <td>303.0978</td>\n",
       "      <td>1063.9902</td>\n",
       "      <td>659.8598</td>\n",
       "      <td>404.1304</td>\n",
       "      <td>24.4337</td>\n",
       "      <td>15.8894</td>\n",
       "      <td>103.2811</td>\n",
       "      <td>21.4357</td>\n",
       "      <td>75.5496</td>\n",
       "      <td>...</td>\n",
       "      <td>585.90</td>\n",
       "      <td>84.42</td>\n",
       "      <td>57.96</td>\n",
       "      <td>6.30</td>\n",
       "      <td>63504.0</td>\n",
       "      <td>2595.6</td>\n",
       "      <td>2721.6</td>\n",
       "      <td>65.520</td>\n",
       "      <td>10508.4</td>\n",
       "      <td>11718.0</td>\n",
       "      <td>1688.4</td>\n",
       "      <td>1159.2</td>\n",
       "      <td>126.0</td>\n",
       "      <td>106.09</td>\n",
       "      <td>111.24</td>\n",
       "      <td>2.6780</td>\n",
       "      <td>429.51</td>\n",
       "      <td>478.95</td>\n",
       "      <td>69.01</td>\n",
       "      <td>47.38</td>\n",
       "      <td>5.15</td>\n",
       "      <td>116.64</td>\n",
       "      <td>2.8080</td>\n",
       "      <td>450.36</td>\n",
       "      <td>502.20</td>\n",
       "      <td>72.36</td>\n",
       "      <td>49.68</td>\n",
       "      <td>5.40</td>\n",
       "      <td>0.067600</td>\n",
       "      <td>10.8420</td>\n",
       "      <td>12.0900</td>\n",
       "      <td>1.7420</td>\n",
       "      <td>1.1960</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>1738.89</td>\n",
       "      <td>1939.05</td>\n",
       "      <td>279.39</td>\n",
       "      <td>191.82</td>\n",
       "      <td>20.85</td>\n",
       "      <td>2162.25</td>\n",
       "      <td>311.55</td>\n",
       "      <td>213.90</td>\n",
       "      <td>23.25</td>\n",
       "      <td>44.89</td>\n",
       "      <td>30.82</td>\n",
       "      <td>3.35</td>\n",
       "      <td>21.16</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.25</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2304</td>\n",
       "      <td>963.36</td>\n",
       "      <td>709.44</td>\n",
       "      <td>3637.92</td>\n",
       "      <td>1090.56</td>\n",
       "      <td>3746.40</td>\n",
       "      <td>2007.84</td>\n",
       "      <td>1738.56</td>\n",
       "      <td>55.20</td>\n",
       "      <td>46.56</td>\n",
       "      <td>257.76</td>\n",
       "      <td>60.96</td>\n",
       "      <td>175.20</td>\n",
       "      <td>233.76</td>\n",
       "      <td>3720.00</td>\n",
       "      <td>16569.84</td>\n",
       "      <td>2.40</td>\n",
       "      <td>147.120</td>\n",
       "      <td>1.92</td>\n",
       "      <td>78.72</td>\n",
       "      <td>80.16</td>\n",
       "      <td>243.36</td>\n",
       "      <td>247.20</td>\n",
       "      <td>5088.0</td>\n",
       "      <td>16.992</td>\n",
       "      <td>3297.6</td>\n",
       "      <td>988.8</td>\n",
       "      <td>14352.0</td>\n",
       "      <td>796.8</td>\n",
       "      <td>15168.0</td>\n",
       "      <td>532.8</td>\n",
       "      <td>672.0</td>\n",
       "      <td>16.800</td>\n",
       "      <td>2716.8</td>\n",
       "      <td>1588.8</td>\n",
       "      <td>436.8</td>\n",
       "      <td>28.8</td>\n",
       "      <td>28.8</td>\n",
       "      <td>402.8049</td>\n",
       "      <td>296.6346</td>\n",
       "      <td>1521.1053</td>\n",
       "      <td>455.9904</td>\n",
       "      <td>1566.4635</td>\n",
       "      <td>839.5281</td>\n",
       "      <td>726.9354</td>\n",
       "      <td>23.0805</td>\n",
       "      <td>19.4679</td>\n",
       "      <td>107.7759</td>\n",
       "      <td>25.4889</td>\n",
       "      <td>73.2555</td>\n",
       "      <td>...</td>\n",
       "      <td>549.46</td>\n",
       "      <td>151.06</td>\n",
       "      <td>9.96</td>\n",
       "      <td>9.96</td>\n",
       "      <td>99856.0</td>\n",
       "      <td>3507.6</td>\n",
       "      <td>4424.0</td>\n",
       "      <td>110.600</td>\n",
       "      <td>17885.6</td>\n",
       "      <td>10459.6</td>\n",
       "      <td>2875.6</td>\n",
       "      <td>189.6</td>\n",
       "      <td>189.6</td>\n",
       "      <td>123.21</td>\n",
       "      <td>155.40</td>\n",
       "      <td>3.8850</td>\n",
       "      <td>628.26</td>\n",
       "      <td>367.41</td>\n",
       "      <td>101.01</td>\n",
       "      <td>6.66</td>\n",
       "      <td>6.66</td>\n",
       "      <td>196.00</td>\n",
       "      <td>4.9000</td>\n",
       "      <td>792.40</td>\n",
       "      <td>463.40</td>\n",
       "      <td>127.40</td>\n",
       "      <td>8.40</td>\n",
       "      <td>8.40</td>\n",
       "      <td>0.122500</td>\n",
       "      <td>19.8100</td>\n",
       "      <td>11.5850</td>\n",
       "      <td>3.1850</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>3203.56</td>\n",
       "      <td>1873.46</td>\n",
       "      <td>515.06</td>\n",
       "      <td>33.96</td>\n",
       "      <td>33.96</td>\n",
       "      <td>1095.61</td>\n",
       "      <td>301.21</td>\n",
       "      <td>19.86</td>\n",
       "      <td>19.86</td>\n",
       "      <td>82.81</td>\n",
       "      <td>5.46</td>\n",
       "      <td>5.46</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 742 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    年龄*年龄  年龄**天门冬氨酸氨基转换酶  年龄**丙氨酸氨基转换酶  年龄**碱性磷酸酶  年龄**r-谷氨酰基转换酶  年龄**总蛋白  \\\n",
       "id                                                                           \n",
       "1    1681         1023.36        947.10    4083.19         829.43  3152.08   \n",
       "2    1681         1007.37       1486.25    2755.61        3239.00  3256.63   \n",
       "3    2116          957.72        700.58    2929.74        1755.82  3966.58   \n",
       "4     484          329.78        232.98    1629.76         444.84  1561.56   \n",
       "5    2304          963.36        709.44    3637.92        1090.56  3746.40   \n",
       "\n",
       "     年龄*白蛋白  年龄**球蛋白  年龄*白球比例  年龄*甘油三酯  年龄*总胆固醇  年龄*高密度脂蛋白胆固醇  年龄*低密度脂蛋白胆固醇  \\\n",
       "id                                                                            \n",
       "1   2033.60  1118.48    74.62    53.71   181.63         56.17        108.65   \n",
       "2   1958.16  1298.47    61.91   115.21   166.46         38.13        107.83   \n",
       "3   2208.00  1758.58    57.96    45.54   189.98         75.44         92.46   \n",
       "4    968.44   593.12    35.86    23.32   151.58         31.46        110.88   \n",
       "5   2007.84  1738.56    55.20    46.56   257.76         60.96        175.20   \n",
       "\n",
       "     年龄*尿素    年龄*肌酐     年龄*尿酸  年龄*乙肝表面抗原  年龄*乙肝表面抗体  年龄*乙肝e抗原  年龄*乙肝e抗体  \\\n",
       "id                                                                        \n",
       "1   240.67  3167.25  14324.99       2.05    125.665      1.64     67.24   \n",
       "2   215.66  3571.92  19957.98       2.05    125.665      1.64     67.24   \n",
       "3   219.42  3596.74  20795.22       0.46      0.920      0.46     63.02   \n",
       "4    93.06  1352.12   8114.70       1.10     67.430      0.88     36.08   \n",
       "5   233.76  3720.00  16569.84       2.40    147.120      1.92     78.72   \n",
       "\n",
       "    年龄*乙肝核心抗体  年龄*白细胞计数  年龄*红细胞计数  年龄*血红蛋白  年龄*红细胞压积  年龄*红细胞平均体积  \\\n",
       "id                                                                 \n",
       "1       68.47    218.94    213.61   6810.1    19.639      3767.9   \n",
       "2       68.47    313.65    213.61   6396.0    18.696      3587.5   \n",
       "3       49.22    211.60    218.96   6844.8    20.148      4227.4   \n",
       "4       36.74    205.92     94.38   3014.0     8.866      2065.8   \n",
       "5       80.16    243.36    247.20   5088.0    16.992      3297.6   \n",
       "\n",
       "    年龄*红细胞平均血红蛋白量  年龄*红细胞平均血红蛋白浓度  年龄*红细胞体积分布宽度  年龄*血小板计数  年龄*血小板平均体积  \\\n",
       "id                                                                      \n",
       "1          1307.9         14227.0         524.8    6806.0       405.9   \n",
       "2          1225.9         14022.0         549.4   11357.0       377.2   \n",
       "3          1439.8         15640.0         598.0   11086.0       381.8   \n",
       "4           701.8          7480.0         277.2    5544.0       226.6   \n",
       "5           988.8         14352.0         796.8   15168.0       532.8   \n",
       "\n",
       "    年龄*血小板体积分布宽度  年龄*血小板比积  年龄*中性粒细胞%  年龄*淋巴细胞%  年龄*单核细胞%  年龄*嗜酸细胞%  年龄*嗜碱细胞%  \\\n",
       "id                                                                              \n",
       "1          713.4     6.724     2218.1    1402.2     266.5     192.7      24.6   \n",
       "2          422.3    10.660     2132.0    1504.7     237.8     192.7      32.8   \n",
       "3          763.6     9.154     2212.6    1853.8     354.2     147.2      36.8   \n",
       "4          237.6     5.720      917.4    1023.0     147.4     101.2      11.0   \n",
       "5          672.0    16.800     2716.8    1588.8     436.8      28.8      28.8   \n",
       "\n",
       "    *天门冬氨酸氨基转换酶**天门冬氨酸氨基转换酶  *天门冬氨酸氨基转换酶**丙氨酸氨基转换酶  *天门冬氨酸氨基转换酶**碱性磷酸酶  \\\n",
       "id                                                                       \n",
       "1                  623.0016               576.5760           2485.7664   \n",
       "2                  603.6849               890.6625           1651.3497   \n",
       "3                  433.4724               317.0886           1326.0258   \n",
       "4                  224.7001               158.7441           1110.4592   \n",
       "5                  402.8049               296.6346           1521.1053   \n",
       "\n",
       "    *天门冬氨酸氨基转换酶**r-谷氨酰基转换酶  *天门冬氨酸氨基转换酶**总蛋白  *天门冬氨酸氨基转换酶*白蛋白  \\\n",
       "id                                                              \n",
       "1                 504.9408         1918.9248        1238.0160   \n",
       "2                1941.0300         1951.5951        1173.4632   \n",
       "3                 794.6994         1795.3086         999.3600   \n",
       "4                 303.0978         1063.9902         659.8598   \n",
       "5                 455.9904         1566.4635         839.5281   \n",
       "\n",
       "    *天门冬氨酸氨基转换酶**球蛋白  *天门冬氨酸氨基转换酶*白球比例  *天门冬氨酸氨基转换酶*甘油三酯  *天门冬氨酸氨基转换酶*总胆固醇  \\\n",
       "id                                                                           \n",
       "1           680.9088           45.4272           32.6976          110.5728   \n",
       "2           778.1319           37.1007           69.0417           99.7542   \n",
       "3           795.9486           26.2332           20.6118           85.9866   \n",
       "4           404.1304           24.4337           15.8894          103.2811   \n",
       "5           726.9354           23.0805           19.4679          107.7759   \n",
       "\n",
       "    *天门冬氨酸氨基转换酶*高密度脂蛋白胆固醇  *天门冬氨酸氨基转换酶*低密度脂蛋白胆固醇 ...  红细胞体积分布宽度*淋巴细胞%  \\\n",
       "id                                               ...                    \n",
       "1                 34.1952                66.1440 ...           437.76   \n",
       "2                 22.8501                64.6191 ...           491.78   \n",
       "3                 34.1448                41.8482 ...           523.90   \n",
       "4                 21.4357                75.5496 ...           585.90   \n",
       "5                 25.4889                73.2555 ...           549.46   \n",
       "\n",
       "    红细胞体积分布宽度*单核细胞%  红细胞体积分布宽度*嗜酸细胞%  红细胞体积分布宽度*嗜碱细胞%  血小板计数*血小板计数  \\\n",
       "id                                                                   \n",
       "1             83.20            60.16             7.68      27556.0   \n",
       "2             77.72            62.98            10.72      76729.0   \n",
       "3            100.10            41.60            10.40      58081.0   \n",
       "4             84.42            57.96             6.30      63504.0   \n",
       "5            151.06             9.96             9.96      99856.0   \n",
       "\n",
       "    血小板计数*血小板平均体积  血小板计数*血小板体积分布宽度  血小板计数*血小板比积  血小板计数*中性粒细胞%  血小板计数*淋巴细胞%  \\\n",
       "id                                                                           \n",
       "1          1643.4           2888.4       27.224        8980.6       5677.2   \n",
       "2          2548.4           2853.1       72.020       14404.0      10165.9   \n",
       "3          2000.3           4000.6       47.959       11592.1       9712.3   \n",
       "4          2595.6           2721.6       65.520       10508.4      11718.0   \n",
       "5          3507.6           4424.0      110.600       17885.6      10459.6   \n",
       "\n",
       "    血小板计数*单核细胞%  血小板计数*嗜酸细胞%  血小板计数*嗜碱细胞%  血小板平均体积*血小板平均体积  血小板平均体积*血小板体积分布宽度  \\\n",
       "id                                                                              \n",
       "1        1079.0        780.2         99.6            98.01             172.26   \n",
       "2        1606.6       1301.9        221.6            84.64              94.76   \n",
       "3        1855.7        771.2        192.8            68.89             137.78   \n",
       "4        1688.4       1159.2        126.0           106.09             111.24   \n",
       "5        2875.6        189.6        189.6           123.21             155.40   \n",
       "\n",
       "    血小板平均体积*血小板比积  血小板平均体积*中性粒细胞%  血小板平均体积*淋巴细胞%  血小板平均体积*单核细胞%  \\\n",
       "id                                                                \n",
       "1          1.6236          535.59         338.58          64.35   \n",
       "2          2.3920          478.40         337.64          53.36   \n",
       "3          1.6517          399.23         334.49          63.91   \n",
       "4          2.6780          429.51         478.95          69.01   \n",
       "5          3.8850          628.26         367.41         101.01   \n",
       "\n",
       "    血小板平均体积*嗜酸细胞%  血小板平均体积*嗜碱细胞%  血小板体积分布宽度*血小板体积分布宽度  血小板体积分布宽度*血小板比积  \\\n",
       "id                                                                       \n",
       "1           46.53           5.94               302.76           2.8536   \n",
       "2           43.24           7.36               106.09           2.6780   \n",
       "3           26.56           6.64               275.56           3.3034   \n",
       "4           47.38           5.15               116.64           2.8080   \n",
       "5            6.66           6.66               196.00           4.9000   \n",
       "\n",
       "    血小板体积分布宽度*中性粒细胞%  血小板体积分布宽度*淋巴细胞%  血小板体积分布宽度*单核细胞%  血小板体积分布宽度*嗜酸细胞%  \\\n",
       "id                                                                        \n",
       "1             941.34           595.08           113.10            81.78   \n",
       "2             535.60           378.01            59.74            48.41   \n",
       "3             798.46           668.98           127.82            53.12   \n",
       "4             450.36           502.20            72.36            49.68   \n",
       "5             792.40           463.40           127.40             8.40   \n",
       "\n",
       "    血小板体积分布宽度*嗜碱细胞%  血小板比积*血小板比积  血小板比积*中性粒细胞%  血小板比积*淋巴细胞%  血小板比积*单核细胞%  \\\n",
       "id                                                                         \n",
       "1             10.44     0.026896        8.8724       5.6088       1.0660   \n",
       "2              8.24     0.067600       13.5200       9.5420       1.5080   \n",
       "3             13.28     0.039601        9.5719       8.0197       1.5323   \n",
       "4              5.40     0.067600       10.8420      12.0900       1.7420   \n",
       "5              8.40     0.122500       19.8100      11.5850       3.1850   \n",
       "\n",
       "    血小板比积*嗜酸细胞%  血小板比积*嗜碱细胞%  中性粒细胞%*中性粒细胞%  中性粒细胞%*淋巴细胞%  中性粒细胞%*单核细胞%  \\\n",
       "id                                                                        \n",
       "1        0.7708       0.0984        2926.81       1850.22        351.65   \n",
       "2        1.2220       0.2080        2704.00       1908.40        301.60   \n",
       "3        0.6368       0.1592        2313.61       1938.43        370.37   \n",
       "4        1.1960       0.1300        1738.89       1939.05        279.39   \n",
       "5        0.2100       0.2100        3203.56       1873.46        515.06   \n",
       "\n",
       "    中性粒细胞%*嗜酸细胞%  中性粒细胞%*嗜碱细胞%  淋巴细胞%*淋巴细胞%  淋巴细胞%*单核细胞%  淋巴细胞%*嗜酸细胞%  \\\n",
       "id                                                                      \n",
       "1         254.27         32.46      1169.64       222.30       160.74   \n",
       "2         244.40         41.60      1346.89       212.86       172.49   \n",
       "3         153.92         38.48      1624.09       310.31       128.96   \n",
       "4         191.82         20.85      2162.25       311.55       213.90   \n",
       "5          33.96         33.96      1095.61       301.21        19.86   \n",
       "\n",
       "    淋巴细胞%*嗜碱细胞%  单核细胞%*单核细胞%  单核细胞%*嗜酸细胞%  单核细胞%*嗜碱细胞%  嗜酸细胞%*嗜酸细胞%  \\\n",
       "id                                                                    \n",
       "1         20.52        42.25        30.55         3.90        22.09   \n",
       "2         29.36        33.64        27.26         4.64        22.09   \n",
       "3         32.24        59.29        24.64         6.16        10.24   \n",
       "4         23.25        44.89        30.82         3.35        21.16   \n",
       "5         19.86        82.81         5.46         5.46         0.36   \n",
       "\n",
       "    嗜酸细胞%*嗜碱细胞%  嗜碱细胞%*嗜碱细胞%  年龄  \n",
       "id                                \n",
       "1          2.82         0.36  41  \n",
       "2          3.76         0.64  41  \n",
       "3          2.56         0.64  46  \n",
       "4          2.30         0.25  22  \n",
       "5          0.36         0.36  48  \n",
       "\n",
       "[5 rows x 742 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "most_important = feature_importance['feature'].loc[:50]\n",
    "poly = PolynomialFeatures(2)\n",
    "train_data_most_important = pd.DataFrame(poly.fit_transform(train_data[most_important]),index=train_data.index)\n",
    "train_data = pd.concat([train_data,train_data_most_important],axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# XGBoost做回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAd8AAAFKCAYAAABcq1WoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ng43EFuIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27f6bda2b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from xgboost.sklearn import XGBRegressor\n",
    "# from sklearn.metrics import f1_score\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.model_selection import cross_val_score\n",
    "import xgboost as xgb\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.linear_model import ElasticNet,LinearRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.utils import resample\n",
    "\n",
    "#  划分样本集\n",
    "# features= feature_importance['feature'].loc[:1000]\n",
    "train_x,test_x,train_y,test_y = train_test_split(train_data,targets,test_size=0.18,random_state=66)\n",
    "# # 过采样\n",
    "# train_x_minority = train_x[train_y['血糖'] >8]\n",
    "# train_y_minority = train_y[train_y['血糖']>8]\n",
    "# train_minority = resample(pd.concat([train_x_minority,train_y_minority],axis=1),\n",
    "#                                  replace=True,     # sample with replacement\n",
    "#                                  n_samples=int(train_y_minority.shape[0]/2),    \n",
    "#                                  random_state=123) # reproducible results\n",
    "# train_x = pd.concat([train_x,train_minority.drop(['血糖'],axis=1)])\n",
    "# train_y = pd.concat([train_y,pd.DataFrame(train_minority['血糖'])])      \n",
    "#----------------------------------------------------training xgboost-----------------------------------------#\n",
    "dtrain = xgb.DMatrix(train_x,label=train_y)\n",
    "dtest = xgb.DMatrix(test_x)\n",
    "# 交叉验证\n",
    "params={'booster':'gbtree',\n",
    "    'objective': 'reg:linear',\n",
    "    'eval_metric': 'rmse',\n",
    "    'max_depth':3,\n",
    "    'lambda':200,\n",
    "    'subsample':0.75,\n",
    "    'colsample_bytree':0.7,\n",
    "    'eta': 0.008,#0.002\n",
    "    'seed':1024,\n",
    "    'nthread':3,\n",
    "    'reg_alpha':0.1\n",
    "    }\n",
    "\n",
    "# 设置参数\n",
    "watchlist  = [(dtrain,'train')]\n",
    "\n",
    "#通过cv找最佳的nround\n",
    "cv_log = xgb.cv(params,dtrain,num_boost_round=2500,nfold=4,metrics='rmse',early_stopping_rounds=50,seed=1024)\n",
    "# bst_rmse= cv_log['test-rmse-mean'].min()\n",
    "# cv_log['nb'] = cv_log.index\n",
    "# cv_log.index = cv_log['test-rmse-mean']\n",
    "# bst_nb = cv_log.nb.to_dict()[bst_rmse]\n",
    "# model = xgb.train(params,dtrain,num_boost_round=2000,evals=watchlist,early_stopping_rounds=50)\n",
    "#---------------------------------------------特征重要性----------------------------------------------#\n",
    "# importance = model.get_fscore()\n",
    "# importance = sorted(importance.items(), key=operator.itemgetter(1),reverse=True)\n",
    "\n",
    "# feature_importance = pd.DataFrame(importance, columns=['feature', 'fscore'])\n",
    "# # top30\n",
    "# most_important = feature_importance['feature'].loc[:30]\n",
    "#-----------------------------------------------------------------------------------------------------#\n",
    "# pre_y_xgb = model.predict(dtest)\n",
    "# train_new = model.predict(dtrain,pred_leaf=True)\n",
    "# test_new = model.predict(dtest,pred_leaf=True)\n",
    "\n",
    "# enet = ElasticNet(alpha=0.001, l1_ratio=0.005,normalize=True,tol=0.01)\n",
    "# pre_y_ent = enet.fit(train_x, train_y).predict(test_x)\n",
    "# pre_y_xgb_ent = enet.fit(train_new, train_y).predict(test_new)\n",
    "\n",
    "# print(mse(test_y,pre_y_xgb))\n",
    "# print(mse(test_y,pre_y_ent))\n",
    "# print(mse(test_y,pre_y_xgb_ent))\n",
    "\n",
    "# plt.figure(figsize=(15,30))\n",
    "# xgb.plot_importance(cv_log)\n",
    "plt.plot(cv_log.index,cv_log['test-rmse-mean'],label='test_rmse')\n",
    "plt.plot(cv_log.index,cv_log['train-rmse-mean'],label='train_rmse')\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()\n",
    "\n",
    "# 交叉验证输出\n",
    "\n",
    "# pre_train_y = xgb.predict(train_x)\n",
    "# print(mse(train_y,pre_train_y))\n",
    "\n",
    "#predict test set\n",
    "# pre_y = model.predict(dtest)\n",
    "# print(mse(test_y,pre_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 测试集样本的真实值和预测值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA24AAAF4CAYAAAAsQarIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhUKhUCiUOc7/Byd7mKPydYElAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27f02762cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "plt.plot(np.arange(test_y.shape[0])+1,test_y,label='real')\n",
    "plt.plot(np.arange(pre_y_xgb.shape[0])+1,pre_y_xgb,label='predict')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title('测试集')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>feature</th>\n",
       "      <th>fscore</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>红细胞平均体积_红细胞平均血红蛋白浓度</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>红细胞平均体积*红细胞体积分布宽度</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>年龄*白细胞计数</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>*天门冬氨酸氨基转换酶_*丙氨酸氨基转换酶</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>年龄**r-谷氨酰基转换酶</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>年龄*甘油三酯</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>年龄*血红蛋白</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>年龄_尿酸</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>*碱性磷酸酶_单核细胞%</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>尿酸*红细胞压积</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>年龄*红细胞计数</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>年龄**丙氨酸氨基转换酶</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>尿素*白细胞计数</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>肌酐_尿酸</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>尿酸*单核细胞%</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>*碱性磷酸酶*低密度脂蛋白胆固醇</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>甘油三酯_乙肝e抗体</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>红细胞平均体积_血小板平均体积</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>血红蛋白_红细胞压积</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>尿酸*血小板比积</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>甘油三酯*乙肝核心抗体</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>红细胞平均血红蛋白浓度_红细胞体积分布宽度</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>甘油三酯_尿酸</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>高密度脂蛋白胆固醇*尿酸</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>*丙氨酸氨基转换酶*甘油三酯</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>*碱性磷酸酶*中性粒细胞%</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>*天门冬氨酸氨基转换酶_血小板体积分布宽度</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>尿酸*血小板计数</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>尿素*乙肝核心抗体</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>尿素_尿酸</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>尿酸*血红蛋白</td>\n",
       "      <td>54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>年龄**碱性磷酸酶</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>红细胞平均血红蛋白量*红细胞体积分布宽度</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>*碱性磷酸酶*尿素</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>尿酸_血红蛋白</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>低密度脂蛋白胆固醇*尿素</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>年龄*中性粒细胞%</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>尿素_乙肝e抗体</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>*天门冬氨酸氨基转换酶*低密度脂蛋白胆固醇</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>红细胞平均体积_红细胞平均血红蛋白量</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>白细胞计数*血小板比积</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>肌酐*尿酸</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>高密度脂蛋白胆固醇_红细胞计数</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>*丙氨酸氨基转换酶_甘油三酯</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>*r-谷氨酰基转换酶_尿酸</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>*碱性磷酸酶_尿酸</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>肌酐_红细胞计数</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>尿酸_血小板体积分布宽度</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>白蛋白_红细胞平均血红蛋白浓度</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>低密度脂蛋白胆固醇_尿酸</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>*天门冬氨酸氨基转换酶*红细胞体积分布宽度</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  feature  fscore\n",
       "0     红细胞平均体积_红细胞平均血红蛋白浓度     266\n",
       "1       红细胞平均体积*红细胞体积分布宽度     183\n",
       "2                年龄*白细胞计数     138\n",
       "3   *天门冬氨酸氨基转换酶_*丙氨酸氨基转换酶     136\n",
       "4           年龄**r-谷氨酰基转换酶     129\n",
       "5                 年龄*甘油三酯     127\n",
       "6                 年龄*血红蛋白     127\n",
       "7                   年龄_尿酸     125\n",
       "8            *碱性磷酸酶_单核细胞%     118\n",
       "9                尿酸*红细胞压积     114\n",
       "10               年龄*红细胞计数     109\n",
       "11           年龄**丙氨酸氨基转换酶      99\n",
       "12               尿素*白细胞计数      94\n",
       "13                  肌酐_尿酸      94\n",
       "14               尿酸*单核细胞%      90\n",
       "15       *碱性磷酸酶*低密度脂蛋白胆固醇      87\n",
       "16             甘油三酯_乙肝e抗体      84\n",
       "17        红细胞平均体积_血小板平均体积      84\n",
       "18             血红蛋白_红细胞压积      79\n",
       "19               尿酸*血小板比积      78\n",
       "20            甘油三酯*乙肝核心抗体      77\n",
       "21  红细胞平均血红蛋白浓度_红细胞体积分布宽度      76\n",
       "22                甘油三酯_尿酸      68\n",
       "23           高密度脂蛋白胆固醇*尿酸      68\n",
       "24         *丙氨酸氨基转换酶*甘油三酯      65\n",
       "25          *碱性磷酸酶*中性粒细胞%      64\n",
       "26  *天门冬氨酸氨基转换酶_血小板体积分布宽度      62\n",
       "27               尿酸*血小板计数      60\n",
       "28              尿素*乙肝核心抗体      57\n",
       "29                  尿素_尿酸      55\n",
       "30                尿酸*血红蛋白      54\n",
       "31              年龄**碱性磷酸酶      52\n",
       "32   红细胞平均血红蛋白量*红细胞体积分布宽度      49\n",
       "33              *碱性磷酸酶*尿素      47\n",
       "34                尿酸_血红蛋白      47\n",
       "35           低密度脂蛋白胆固醇*尿素      44\n",
       "36              年龄*中性粒细胞%      43\n",
       "37               尿素_乙肝e抗体      43\n",
       "38  *天门冬氨酸氨基转换酶*低密度脂蛋白胆固醇      43\n",
       "39     红细胞平均体积_红细胞平均血红蛋白量      42\n",
       "40            白细胞计数*血小板比积      41\n",
       "41                  肌酐*尿酸      41\n",
       "42        高密度脂蛋白胆固醇_红细胞计数      40\n",
       "43         *丙氨酸氨基转换酶_甘油三酯      40\n",
       "44          *r-谷氨酰基转换酶_尿酸      40\n",
       "45              *碱性磷酸酶_尿酸      40\n",
       "46               肌酐_红细胞计数      40\n",
       "47           尿酸_血小板体积分布宽度      38\n",
       "48        白蛋白_红细胞平均血红蛋白浓度      37\n",
       "49           低密度脂蛋白胆固醇_尿酸      37\n",
       "50  *天门冬氨酸氨基转换酶*红细胞体积分布宽度      37"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importance.loc[:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "importance = model.get_fscore()\n",
    "importance = sorted(importance.items(), key=operator.itemgetter(1),reverse=True)\n",
    "feature_importance = pd.DataFrame(importance, columns=['feature', 'fscore'])\n",
    "feature_importance.to_csv('../feature_importance.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAdkAAAFKCAYAAABRtSXvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116d5714320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(cv_log.index,cv_log['test-rmse-mean'],label='test_rmse')\n",
    "plt.plot(cv_log.index,cv_log['train-rmse-mean'],label='train_rmse')\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 先分类再回归\n",
    "先将一些异常大的值（长尾）数据作一个分类，分类训练模型，不同的类训练不同的回归模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.13789319864\n"
     ]
    }
   ],
   "source": [
    "pre_y[pre_label > np.sort(pre_label)[pre_label.shape[0] - 60]] = tau\n",
    "#predict test set\n",
    "# pre_y = model.predict(dtest)\n",
    "print(mse(test_y,pre_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAewAAAFKCAYAAADfb2yTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1eeae7f1128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import xgboost as xgb\n",
    "train_x,test_x,train_y,test_y = train_test_split(train_data,targets,test_size=0.18,random_state=66)\n",
    "tau = 7.5\n",
    "scale_weight = float(len(train_label)-train_label.sum())/train_label.sum()\n",
    "proba_tau = int(test_x.shape[0]/scale_weight)\n",
    "train_label = np.where(train_y>tau,1,0)\n",
    "test_label = np.where(test_y>tau,1,0)\n",
    "dtrain = xgb.DMatrix(train_x,label=train_label)\n",
    "dtest = xgb.DMatrix(test_x)\n",
    "watchlist  = [(dtrain,'train')]\n",
    "params={'booster':'gbtree',\n",
    "    'objective': 'binary:logistic',\n",
    "    'scale_pos_weight':scale_weight,\n",
    "    'eval_metric': 'auc',\n",
    "    'max_depth':6,\n",
    "    'lambda':70,\n",
    "    'subsample':0.6,\n",
    "    'colsample_bytree':0.6,\n",
    "    'eta': 0.001,\n",
    "    'seed':1024,\n",
    "    'nthread':3\n",
    "    }\n",
    "model = xgb.train(params,dtrain,num_boost_round=120,evals=watchlist)\n",
    "pre_label = model.predict(dtest)\n",
    "pre_y[pre_label > np.sort(pre_label)[pre_label.shape[0] - proba_tau]] = tau\n",
    "plt.plot(cv_log.index,cv_log['test-auc-mean'],label='test_auc')\n",
    "plt.plot(cv_log.index,cv_log['train-auc-mean'],label='train_auc')\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "feature_50 = df_feature.sort_values('feature_important',ascending=False)[:50]['features']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train = train_data.copy()\n",
    "train_data = train_data[feature_50]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GBDT做回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py:526: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_mse: 2.11885561632\n",
      "train_mse: 1.18575411877\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWIAAAGECAYAAAAMQSrlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSDEkxARBECnm/wPtpvZ3v1NzVwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a502f9ce48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArcAAAReCAYAAADNBhgHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a501534048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "# from sklearn.metrics import f1_score\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "\n",
    "# poly = PolynomialFeatures(2)\n",
    "# data = poly.fit_transform(train_data)\n",
    "\n",
    "# Fit regression mo#  划分样本集\n",
    "\n",
    "train_x,test_x,train_y,test_y = train_test_split(train_data,targets,test_size=0.18,random_state=66)\n",
    "def learner(clf):\n",
    "    # 训练\n",
    "    clf.fit(train_x, train_y)\n",
    "\n",
    "    # 预测\n",
    "    pre_y = clf.predict(test_x)\n",
    "    print('test_mse:',mse(test_y,pre_y))\n",
    "    pre_train_y = clf.predict(train_x)\n",
    "    print('train_mse:',mse(train_y,pre_train_y))\n",
    "    return clf,pre_y,pre_train_y\n",
    "# 设置参数\n",
    "params = {'n_estimators': 300, 'max_depth': 4, 'min_samples_split': 10,'subsample':0.8,'max_features':'log2','max_leaf_nodes':5,\n",
    "          'learning_rate': 0.04, 'loss': 'ls','warm_start':True}\n",
    "gbdt = GradientBoostingRegressor(**params)\n",
    "(gbdt,pre_y,pre_train_y) = learner(gbdt)\n",
    "# param_grid = [{'criterion':[3,4]}]\n",
    "# grid_search = GridSearchCV(gbdt,param_grid,cv=4,scoring='neg_mean_squared_error')\n",
    "# grid_search.fit(train_x,train_y)\n",
    "# # 交叉验证输出\n",
    "# print('grid_scores_',grid_search.grid_scores_)\n",
    "# print('best_pram',grid_search.best_estimator_)\n",
    "# # 预测\n",
    "# pre_y = grid_search.predict(test_x)\n",
    "# print(mse(test_y,pre_y))\n",
    "# pre_train_y = grid_search.predict(train_x)\n",
    "# print(mse(train_y,pre_train_y))\n",
    "# 训练\n",
    "# xgb.fit(train_x, train_y)\n",
    "# pre_y = xgb.predict(test_x)\n",
    "\n",
    "\n",
    "test_score = np.zeros((params['n_estimators'],), dtype=np.float64)\n",
    "for i, pre_y in enumerate(gbdt.staged_predict(test_x)):\n",
    "    test_score[i] = mse(test_y, pre_y)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.title('Deviance')\n",
    "plt.plot(np.arange(params['n_estimators']) + 1, gbdt.train_score_, 'b-',\n",
    "         label='Training Set Deviance')\n",
    "plt.plot(np.arange(params['n_estimators']) + 1, test_score, 'r-',\n",
    "         label='Test Set Deviance')\n",
    "plt.legend(loc='upper right')\n",
    "plt.xlabel('Boosting Iterations')\n",
    "plt.ylabel('Deviance')\n",
    "# 画出特征重要性图\n",
    "features = list(train_data.columns)\n",
    "feature_important = gbdt.feature_importances_\n",
    "df_feature = pd.DataFrame({'features':features,'feature_important':feature_important})\n",
    "df_feature.sort_values(by='feature_important',inplace=True)\n",
    "plt.figure(figsize=(10,20))\n",
    "plt.barh(np.arange(len(features)),df_feature['feature_important'])\n",
    "plt.yticks(np.arange(len(features)),df_feature['features'],fontsize=9,rotation=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 测试集样本的真实值和预测值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# train_data.loc[big_error_index.index].sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "big_error_index = test_y[np.square(error)>2]\n",
    "with open('big_error_index.pickle', 'wb') as f:\n",
    "     pickle.dump(big_error_index, f)\n",
    "# test_y.index[np.square(error)>2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA24AAAF4CAYAAAAsQarIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27f00684588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2QAAAF4CAYAAAA7YzoBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27f0091f278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,6))\n",
    "plt.plot(np.arange(test_y.shape[0])+1,test_y,label='real')\n",
    "plt.plot(np.arange(pre_y.shape[0])+1,pre_y,label='predict')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title('测试集')\n",
    "plt.show()\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.plot(np.arange(train_y.shape[0])+1,train_y,label='real')\n",
    "plt.plot(np.arange(pre_train_y.shape[0])+1,pre_train_y,label='predict')\n",
    "plt.legend(loc='upper right')\n",
    "plt.title('训练集')\n",
    "plt.show()\n",
    "# sns.distplot(test_y,label='test_y')\n",
    "# sns.distplot(pre_y,label='pre_y')\n",
    "# plt.title('测试集')\n",
    "# plt.show()\n",
    "# sns.distplot(train_y,label='train_y')\n",
    "# sns.distplot(pre_train_y,label='pre_train_y')\n",
    "# plt.title('训练集')\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 弹性网做回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.23396668253\n",
      "2.07841542885\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import ElasticNet,LinearRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "def mse_cv(model):\n",
    "    mse= -cross_val_score(model, train_data, targets, scoring=\"neg_mean_squared_error\", cv = 5)\n",
    "    return(mse)\n",
    "\n",
    "train_x,test_x,train_y,test_y = train_test_split(train_data,targets,test_size=0.18,random_state=66)\n",
    "enet = ElasticNet(alpha=0.01, l1_ratio=0.05,normalize=True,tol=0.01)\n",
    "\n",
    "pre_y = enet.fit(train_x, train_y).predict(test_x)\n",
    "# 预测\n",
    "# pre_y[pre_y >30] = 30\n",
    "# pre_y[pre_y<3] = 3\n",
    "print(mse(test_y,pre_y))\n",
    "pre_train_y = enet.predict(train_x)\n",
    "print(mse(train_y,pre_train_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.63441526324\n",
      "1.61646358852\n"
     ]
    }
   ],
   "source": [
    "pre_y[pre_y >30] = 30\n",
    "pre_y[pre_y<3] = 3\n",
    "print(mse(test_y,pre_y))\n",
    "pre_train_y = enet.predict(train_x)\n",
    "print(mse(train_y,pre_train_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# targets.sort_values('血糖',ascending=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
